Personalized Shopping: How Well Are You Paying Attention to Customer Data?

Personalized Shopping: How Well Are You Paying Attention to Customer Data?
The following is a guest contribution from Bridge Mellichamp of StitchLabs

Are you stuck in a one sided relationship with the brands you love?

It’s a growing epidemic: You’re in the mood to shop, so you open your inbox to see if any of the latest trends from your favorite retailers and brands catch your eye.

You select an email with a subject line promising the latest spring fashions, but your excitement deflates when the content is focused entirely on prom season.

You might be thrilled if you were a teenage girl. However; you’re a single, 28- year-old man who was stood-up at prom the first time around. You’re over it, of course, but you still get a little bitter around prom seasons.

What’s worse though, is you can’t believe that in this day and age, the only detail the email got right was your name and the correct zip code for the nearest store. Who does this retailer think you are? Why won’t they take the time to get to know you?

Disappointed that you weren’t delighted by content that was supposed to be tailored just for you, you unsubscribe from this brand’s mailing list and continue clicking through your messages.

It’s not a pleasant experience, and downright unnecessary in the age of Big Data. When customers shop, they provide the retailer with information about themselves, as well as their preferences, interests, and buying habits.

Where we, as retailers, really drop the ball is by not doing anything with this data.

From not wasting a customer’s time by sending them irrelevant emails, all the way down to the way you display product pricing on your website, data can help predict, inform, and delight your customers, and can greatly improve their experience with your brand.

What Do Customers Really Want?

We live in an age of frightening transparency. Between social media, fast data connections, and a mini-computer in everyone’s hand, there are more ways for customers to discover, research, and purchase items. And the more ways shoppers can interact, the more data you have at your fingertips.

Customer data can be used to create behavioral models for your shoppers and illuminate opportunities for personalization at each of your customer touch points. But it's not enough to simply collect this data; you have to ask the right questions of it, then take appropriate actions based on the insights you’ve gleaned if you want it to have any impact.

This may seem obvious, but often retailers make assumptions about what their customers actually want without validating their best guesses. For example, with nearly half of all American households having at least one subscriber to Amazon Prime, it could be easy to assume that delivery speed is of the utmost importance to customers.

However, a Customer Experience Report by RightNow found that the #1 reason customers would abandon a brand was due to poor quality and rude customer service. These reasons were cited 18% more often than “slow or untimely service.” Even if you aren’t the speediest retailer in town, it might pay to ensure that the lack of speed is counterbalanced with exceptional customer service.

What  else do your customers want? The products they see listed on your site.

Data is a crucial tool for forecasting and planning to ensure customers can get what they want, when they want it.

Seventy-five percent of U.S. adults have come across an unavailable product in stores over the past year, with 63% encountering that issue online. As a result, the majority of these frustrated shoppers decided to shop at another retailer or buy nothing at all.

The combined impact of overstocks, out-of-stocks, and preventable returns adds up to 11.7% of lost annual revenue to most retailers.

Using data to understand how a customer thinks extends beyond service and logistics. From anticipating customer needs to testing and personalizing communications, successful retailers are using data to make more informed business decisions.

More Data Means Higher Expectations

With more data available than ever before, customers expect an efficient, personalized experience.

As Jason McNeillis, VP of Product Strategy at RedPoint Global, puts it, we need “to use all that data to deliver the optimal customer experience for a specific customer at that moment of truth.”

So what can you do today to optimize your customer experience using data?

Anticipate Customer Needs: Remember the email you got with styles for prom night that could perhaps have been useful ten years ago? Data can ensure this never happens to one of your customers. If they have an account with your online store, you should be able to log in and get a clearer picture of who they are and how they shop.

Have they purchased something recently? Has that item shipped? What emails have they opened from your business in the last few days? Make sure employees review this information before creating a repetitive and frustrating process for the customer.

Target Says "Dad I'm Pregnant" Before Daughter Gets The Chance

In an infamous example of anticipating customer needs, Target managed to figure out a teenage girl was pregnant before her father did.

How did they do it?

Target assigns each customer an ID, and uses it to track that person’s purchase history and buying habits. They found that in the first 20 weeks of pregnancy, women purchase certain supplements and many buy soap and cotton balls.

Based on these buying habits, Target began to send the teenage girl coupons for baby items, creating tension between Target and the girl’s father, who was unaware of his daughter’s pregnancy. While this is an extreme case, Target used Big Data to know exactly what products this customer would need, with a timeline of when she would need them.

This highly personalized timeline gives Target an edge by capturing shoppers at this key life stage with the expectation of capturing a lifetime of purchases for baby.

Personalized Shopping: How Well Are You Paying Attention To Customer Data

You don’t always need Big Data to anticipate customer needs.

Simply paying attention to your customers pays off as well. And understanding what’s important in their lives (for example, promotions for the holidays or back to school shopping) is the first step anyone can take to successfully anticipate customer needs.

For example, Carmine Gallo, a contributor for Forbes, raved about a hotel in San Diego that provided exceptional customer service based on anticipating guests’ needs. As his daughters settled to play in the sand, a hotel staff member quickly dropped sand toys in front of them. On a hot day, their car was loaded with water bottles.

The hotel left such a great impression on Gallo that he shared his experience in the media.

Test to Optimize Experiences: A/B and multivariate testing is a helpful way to experiment with different designs and use data before making a final decision on things like branded websites, email copy, and advertisements.

It also allows your customers to speak for themselves instead of relying on opinions and guesses, which may not accurately reflect their wants and needs. Since A/B testing can directly impact your revenue, from enhancing site conversion to product offerings, it is something your business should absolutely be doing.

Solutions like Optimizely enable you to test and iterate until your website reflects your brand and provides your customers with an authentic experience. While certain details may seem insignificant, sometimes the tiniest changes can have huge impacts.


  • Popular lingerie company Adore Me, which has grown 5,506% in the past three years, tests multiple versions of each photo before they go live on their website. They’ve found that changes as seemingly small as a model moving her hand from her hip to her head can double sales.
  • Mobal, a mobile phone retailer, increased sales by 27% after A/B testing a new line of handsets. This increase wasn’t the result of design changes or cell phone plans, but by  simply adding a new option to their existing line of phone offerings.
  • The Journal of Consumer Psychology found that removing dollar signs, commas, and cents from a listed price make prices appear shorter, and thus less expensive, to consumers. For higher priced items, the test revealed that simply writing the dollar amount versus adding a dollar sign and cents (for example, 100 instead of $100.00), or even test anchoring, by listing a higher price, that was stricken through, with a lower price next to it, make the actual price look like a bargain.

Personalize your Communications: Forty-one percent of consumers in a recent survey said they would buy more from retailers that send them personalized emails.

While adding a customer’s name is a great place to start, determining where they found you, which product(s) they have researched, and knowing their previous order histories are all ways to help you make an email worth reading.

As Facebook CMO, Gary Briggs said, “You know a lot about me. I’m liking things, I’m tweeting things. You should be able to put something relevant in front of me.”

For example, if a customer has liked photos of a bathing suit on social media, send her a promotion for that bathing suit. If she buys the bathing suit, send her targeted ads promoting sunglasses, beach towels, and cover-ups.

Actions like these drive repeat purchases and elevate customer loyalty, which Stitch Labs data recently proved is very profitable for retailers. Personalized, targeted emails are a great tactic to boost return shopper rates  –  and it’s worth the effort. The analysis found that annually, return customers spend over 120% more than new customers.

Personalized Shopping: How Well Are You Paying Attention To Customer Data

If you’re not convinced, here are some more reasons to personalize your customer experience:

  • When customers are segmented for more personalized offers, email open rates increased by 39%, emails were seen as more relevant by 34% of email recipients and unsubscribe rates reduced by 28%.
  • A recent study by MyBuy’s 2015 Personalization Consumer Survey, revealed 53% of consumers purchase more from brands who suggest products based on their browsing or buying behavior, while 49% buy more from brands who personalize online ads that promote offers and products. Forty-eight percent of consumers purchase more from brands who send personalized emails based on past browsing and buying behavior, and from brands who personalize the shopping experience across all channels.

No matter what you’re focused on, from improving operations to increasing customer satisfaction, data can give customers the personalized experience they want.

Be sure to come back over the next few weeks for the remaining three parts of our series, in which we’ll provide our recommendations to help retailers extract actionable insights and implement improvements through smarter data reporting and intelligence.

Personalized Shopping: How Well Are You Paying Attention To Customer DataAbout The Author

Bridge Mellichamp is the Director of Data Science and Special Projects at Stitch Labs. Numbers excite her more than you can imagine; at the core, she’s driven by helping Stitch and its customers make sense of their data so they can make incredibly smart business decisions.